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EP2031348B1 - Procédé d'inspection de surfaces destinée à détecter des défauts de surface et/ou mesurer la topographie de surface - Google Patents

Procédé d'inspection de surfaces destinée à détecter des défauts de surface et/ou mesurer la topographie de surface Download PDF

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Publication number
EP2031348B1
EP2031348B1 EP08012399.5A EP08012399A EP2031348B1 EP 2031348 B1 EP2031348 B1 EP 2031348B1 EP 08012399 A EP08012399 A EP 08012399A EP 2031348 B1 EP2031348 B1 EP 2031348B1
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EP
European Patent Office
Prior art keywords
camera
inspection method
screen
pattern
image
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Not-in-force
Application number
EP08012399.5A
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German (de)
English (en)
Other versions
EP2031348A1 (fr
Inventor
Hagen Krambeer
Ulrich Dr. Müller
Günther Dr. Coen
Jan Dr. Polzer
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
BFI VDEH Institut fuer Angewandte Forschung GmbH
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BFI VDEH Institut fuer Angewandte Forschung GmbH
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Classifications

    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01B—MEASURING LENGTH, THICKNESS OR SIMILAR LINEAR DIMENSIONS; MEASURING ANGLES; MEASURING AREAS; MEASURING IRREGULARITIES OF SURFACES OR CONTOURS
    • G01B11/00—Measuring arrangements characterised by the use of optical techniques
    • G01B11/24—Measuring arrangements characterised by the use of optical techniques for measuring contours or curvatures
    • G01B11/25—Measuring arrangements characterised by the use of optical techniques for measuring contours or curvatures by projecting a pattern, e.g. one or more lines, moiré fringes on the object
    • G01B11/2513—Measuring arrangements characterised by the use of optical techniques for measuring contours or curvatures by projecting a pattern, e.g. one or more lines, moiré fringes on the object with several lines being projected in more than one direction, e.g. grids, patterns
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01B—MEASURING LENGTH, THICKNESS OR SIMILAR LINEAR DIMENSIONS; MEASURING ANGLES; MEASURING AREAS; MEASURING IRREGULARITIES OF SURFACES OR CONTOURS
    • G01B11/00—Measuring arrangements characterised by the use of optical techniques
    • G01B11/30—Measuring arrangements characterised by the use of optical techniques for measuring roughness or irregularity of surfaces
    • G01B11/306—Measuring arrangements characterised by the use of optical techniques for measuring roughness or irregularity of surfaces for measuring evenness
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01M—TESTING STATIC OR DYNAMIC BALANCE OF MACHINES OR STRUCTURES; TESTING OF STRUCTURES OR APPARATUS, NOT OTHERWISE PROVIDED FOR
    • G01M11/00—Testing of optical apparatus; Testing structures by optical methods not otherwise provided for
    • G01M11/005—Testing of reflective surfaces, e.g. mirrors
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/50—Depth or shape recovery
    • G06T7/521—Depth or shape recovery from laser ranging, e.g. using interferometry; from the projection of structured light
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B21—MECHANICAL METAL-WORKING WITHOUT ESSENTIALLY REMOVING MATERIAL; PUNCHING METAL
    • B21B—ROLLING OF METAL
    • B21B38/00—Methods or devices for measuring, detecting or monitoring specially adapted for metal-rolling mills, e.g. position detection, inspection of the product
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B21—MECHANICAL METAL-WORKING WITHOUT ESSENTIALLY REMOVING MATERIAL; PUNCHING METAL
    • B21B—ROLLING OF METAL
    • B21B38/00—Methods or devices for measuring, detecting or monitoring specially adapted for metal-rolling mills, e.g. position detection, inspection of the product
    • B21B38/02—Methods or devices for measuring, detecting or monitoring specially adapted for metal-rolling mills, e.g. position detection, inspection of the product for measuring flatness or profile of strips

Definitions

  • the invention relates to a surface inspection method for detecting surface defects and / or measuring the surface topography of specular continuous surfaces.
  • optical measuring points which work according to the principle of fringe projection are increasingly used for online measurement of the surface.
  • these measurement systems provide the shape of the surface as a matrix Z ij (X i , Y i ). From this, among other things, a so-called longitudinal distribution can be calculated, which in turn is used as a measured variable in the control of a roll stand.
  • the measuring ranges are in practice during strip rolling usually 2 mx 2 m large. Due to the areal measurement at a certain point in time (exposure time of the camera), there is no falsification of the measurement result due to the proper movement of the material to be measured.
  • these measuring systems are only suitable for the measurement of such surfaces which at least partially diffuse light diffusely. The systems can not be used to measure highly reflective surfaces, e.g. As stainless steel or aluminum.
  • a reflective steel apparatus having an inspection unit for measuring planarity errors comprising a camera and a light grid through which light passes from a light source.
  • the device further comprises a moving, reflective metal band.
  • the camera and the light grid are arranged such that the viewing direction of the camera is directed to a region through which a surface of the moving, reflective metal strip is moved.
  • the light grid is arranged and assigned to this area such that the beam path of the viewing beams of the camera leads from the camera over the surface of the reflective metal strip to the surface of the light grid.
  • the focus of the camera is set on the grid.
  • the object of the invention is to propose a surface inspection method for detecting surface defects and / or measuring the surface topography of continuous surfaces, which can also be used for highly reflective surfaces.
  • the method should be designed such that it can be made robust. Ideally, it only needs one shot per measurement. Furthermore, ideally the calibration effort should be minimal.
  • the invention makes use in particular of the property of reflecting surfaces to reflect light rays in accordance with the law of reflection.
  • a camera is provided which is oriented to mirror the image of a likewise provided screen (a faceplate) with a patterned pattern in it surveying, reflective surface looks. If the specular surface is a plane, then the camera receives the pattern of the face plate undistorted. Deviations in the specimen to be mirrored, such as humps, waves, transverse arcs or surface defects, deform the mirror image of the faceplate.
  • the deformation of the pattern of the faceplate in the image taken by the camera can be used to calculate the course of a model surface for the considered, reflecting surface.
  • Surface topography has a camera and a screen on which a pattern is imaged.
  • the viewing direction of the camera is directed to a region through which a surface of the moving, reflective metal strip is moved.
  • the surface of the screen on which the pattern is imaged faces this area so that the beam path of the viewing beams of the camera leads from the camera over the surface of the specular metal strip to the surface of the screen.
  • the camera is focused on the surface of the screen.
  • mirroring refers to a surface or a metal strip in which the reflection law applies. These smooth surfaces have small roughness structures relative to the wavelength of the light. On rough surfaces, the radiation is scattered back diffusely.
  • the camera used is in particular a CCD matrix camera or a camera which is sensitive in the wavelength range of visible light.
  • the device can be equipped with only a single camera, since the surface inspection method according to the invention does not require the observation of the reflecting surfaces from several directions of observation.
  • the device may be configured with a single screen. This can be permanently mounted in the device and does not need to be moved to perform the inspection.
  • the pattern is fixedly applied to the screen, for example printed on the screen. It may be provided a light source that illuminates the screen.
  • the pattern may be projected onto the screen by a projector, such as a projector with a slide advancement.
  • the screen is opaque.
  • the screen can be formed by a backlit LCD display or a plasma screen.
  • the pattern starting from the measuring range, is a homogeneous grid, for example a cross grid.
  • other, non-grid pattern can be used, for example, checkerboard pattern, color-coded pattern, coded marks or dot code.
  • the pattern has a homogeneous grid and at least one mark deviating from the homogeneous grid.
  • the surface inspection method according to the invention it is advantageous if individual elements of the grid can be identified with a continuous index.
  • the provision of a mark deviating from the homogeneous grid makes it particularly easy to determine the starting point of this indexing and also to find it in the camera's image, even if the pattern is reflected differently by the reflecting surface.
  • the pattern has a cross grid, in which the grid interspaces are not rectangular but round. It has been shown that such a cross lattice can be analyzed particularly well.
  • a camera first makes a picture of a pattern formed on a screen, which is designed that it represents at least intersections of lines.
  • the viewing direction of the camera is directed to an area of the reflective surface.
  • the surface of the screen, on which the pattern is shown, faces this area, so that the beam path of the viewing beams of the camera leads from the camera over the reflecting surface to the surface of the screen.
  • the camera is focused on the surface of the screen.
  • the recording is stored as matrix A, in which the respective value a ij corresponds to the measured value which the camera has recorded at the pixel location i ij , wherein the maximum value I of the index i of the number of pixel locations in a first direction of propagation of the receiving surface of the camera and the Maximum value J of the index j of the number of pixel locations in one second propagation direction corresponds.
  • the stored matrix A is converted by a binarization into a matrix B in which the respective value b ij is either 1 or 0.
  • the binary image represented by the matrix B is fed to a skeletonizing process in which, in a coordinate system whose two axes correspond to the two indices of the matrix, line curves are determined along which the values b ij are equal and then an intersection table is generated which represents the spatial Location of intersections of line traces in the coordinate system.
  • an intersection table is generated which represents the spatial Location of intersections of line traces in the coordinate system.
  • the surface inspection method according to the invention is based on the following considerations: Assuming different layers of the reflecting surface ( Fig. 1 ) this means for the viewing beam s of the camera that it sees a different point of the screen in a measured object situated outside the zero plane relative to a defined zero plane than in the zero plane. Although all geometric data (the so-called external calibration) and the parameters are also known by the camera, the local height z can not be calculated directly because the direction of the reflected beam r is missing. The ambiguity arises because only the points of impingement s i of the reflected visual rays r i on the faceplate can be identified.
  • the surface inspection method according to the invention can roughly be subdivided into two superordinate sections, namely the preparation of the image of the camera for generating an intersection table, which reproduces the spatial position of the intersections of lines in the image of the camera in a coordinate system.
  • the course of a model surface for the considered specular surface is determined from the information about the position of these intersections by means of an iterative method.
  • a gray image of a corresponding matrix camera is processed.
  • the intersections of the shot taken by the camera from a crossing grille applied to the screen plate may be presented as a table with its pixel coordinates and grid indices.
  • the direction of the visual rays can be calculated from the pixel coordinates via a camera transformation calculation. Since the position of the crossing points on the screen plate is known and their assignment from the indices from the image processing is possible, a height matrix can be calculated from these geometry data. But there are also other approaches conceivable.
  • the model surface is represented by a two-dimensional Chebyshev polynomial. It has been shown that such a surface representation significantly reduces the computational effort_
  • a camera may take a photograph of a pattern imaged on a screen, which is designed to represent at least intersections of lines.
  • the viewing direction of the camera is directed to a portion of the specular surface.
  • the surface of the screen on which the pattern is imaged is arranged and faces this area so that the beam path of the viewing beams of the camera leads from the camera over the reflecting surface to the surface of the screen.
  • the camera is focused on the surface of the screen.
  • the image is analyzed by an analysis method and an intersection table is generated, which represents the spatial position of intersections of the lines in a coordinate system.
  • the course of a model surface for the considered specular surface is determined from the intersection table, the model surface being represented by a two-dimensional Chebyshev polynomial.
  • the detection of the occurrence of surface defects as well as the detection of the surface topography or of the surface gradients (measurement) are made possible according to the invention. These can be derived from the model surface.
  • the respective intersection point is stored in the intersection table with an index value defining it and its x and y coordinates in a coordinate system. This makes it possible to identify the individual points of intersection and, in the course of the iterative method, to assign respective points of intersection in the pattern on the screen plate.
  • the pattern is fixedly applied to the screen, for example printed on the screen. It may be provided a light source that illuminates the screen.
  • the pattern may be projected onto the screen by a projector, such as a projector with a slide advancement.
  • the screen is opaque.
  • the screen can be formed by a backlit LCD display or a plasma screen.
  • the pattern is a homogeneous grid, for example a cross grid.
  • the formation of the pattern as a grid simplifies the evaluation of the recording of the camera.
  • other, not grid-like patterns may be used, such as checkerboard pattern, color-coded pattern, dot code.
  • the pattern has a homogeneous grid and at least one mark deviating from the homogeneous grid.
  • the surface inspection method according to the invention it is advantageous if individual elements of the grid can be identified with a continuous index.
  • the provision of a mark deviating from the homogeneous grid makes it particularly easy to determine the starting point of this indexing and also to find it in the camera's image, even if the pattern is reflected differently by the reflecting surface.
  • the pattern has a cross grid, in which the grid interspaces are not rectangular but round. It has been shown that such a cross lattice can be analyzed particularly well.
  • the binarization is performed dynamically.
  • a real camera image is usually a uniform illumination does not exist. Therefore, the thresholds between the transition from white to black will not be uniform.
  • the dynamic binarization is preferably carried out region-oriented. The pixels can be triggered in the ratio 1: 1 (white: black).
  • the surface inspection method according to the invention is used in particular in installations for metal strip finishing, but can also be used, for example, for inspecting stainless steel, aluminum, copper, glass panes and mirrors and painted surfaces.
  • a possible pattern for the device according to the invention is in Fig. 3 shown.
  • a cross lattice is used as a binary image with a grid spacing (mesh spacing) of 50 mm x 50 mm.
  • the measuring range is 1.6 mx 1.6 m, for example.
  • the image to be printed on the screen plate is calculated via a screen transformation.
  • the object-level grating has been extended to 3.2m x 3.2m.
  • a marker was used. This serves as entry point for the index counter during the detection routine.
  • Fig. 4 the grid to be printed on the screen plate is shown.
  • Fig. 5 shows the camera when the reflecting surface is completely flat and without any surface defect in the zero level.
  • Fig. 6 shows the recording of the camera with a wavy sheet metal.
  • Fig. 7 shows the flowchart of a two-dimensional image processing.
  • the image is first transformed into the object plane. Subsequently, a binarization with dynamic threshold takes place. All structures in this image are now thinned to the thickness of a pixel: skeletonization. Due to large local distortions of the cross lattice is very expensive to detect the crossing points directly. Therefore, in a next step, horizontal and vertical lines are preferably separated. The individual lines are now fed to a B-spline interpolation. In this way, the intersections of all horizontal lines with all vertical lines can be calculated. The zero markers correctly index the intersection coordinates. These coordinates are still in the object plane, so now follows the inverse transformation into the image plane of the camera. Two matrices with intercept coordinates for x and y are output.
  • the camera image is converted into the object plane via the transformation parameters of the real measuring point ( Fig. 8 ). Now there is a rectangular area, which greatly simplifies the following image processing steps.
  • the transformation parameters are taken from the inner and outer camera calibration.
  • the internal calibration includes: distortion parameters of the camera lens, chip data, focal length.
  • the external calibration includes rotation matrix and translation vector to convert between the coordinate systems of camera and measuring range
  • Fig. 9a shows a section of the image transformed into the object plane according to Fig. 8 .
  • Fig. 9b shows the binarized section.
  • the pixels are grouped into the following classes: Isolated Point, Line Start, Line Element, Node, Inner Point, and Minor Point.
  • Isolated Point For N8 neighborhood relationships, the pixels are grouped into the following classes: Isolated Point, Line Start, Line Element, Node, Inner Point, and Minor Point.
  • Prerequisite for this classification is that only closed lines are available after the binarization ( H. Kazmierczak, Capture and Machine Processing of Image Data, Akademie-Verlag-Berlin, 1980 ).
  • a simplification is made by the shape of the cross lattice. Concave structures are provided in the region of larger curvatures. Therefore, it is not black rectangles, but black circles on a white background.
  • the Fig. 10 shows the result of the skeletonization, wherein the image is shown negated for printing reasons.
  • Skeletonization can be relatively computationally time consuming.
  • the Binarsent is successively cleared from black to white (so-called Opening).
  • Opening In each processing step, neighbor relationships to other pixels must be checked for each pixel.
  • Fig. 11a shows the horizontal lattice portions of the skeletal image and Fig. 11b the vertical grid components. If you follow in Fig. 10 For example, a horizontal line, it is found that this section is more vertical than horizontal and that in this area an overlap to the vertical lines occurs. Thus, two forks are created when an intersection is deformed. The connection of both forks contains both a horizontal and a vertical line. This knowledge of the structure of the deformed cross lattice is considered in the algorithm for separating vertical and horizontal lines.
  • the mark provided in the pattern reproduced on the screen plate results in the photograph after the image processing to two superimposed interruptions in the skeletal image of the horizontal grating portions and two juxtaposed interruptions in the skeletal image of the vertical grating portions. All four interruptions are close together, so that misdetections, due to local disturbances, can virtually be ruled out. A clear indexing of all lines is ensured.
  • intersections of the horizontal and vertical lines are read out and indexed via a grid counter. Starting from the four interruptions described above, all intersection points are counted in horizontal and vertical directions. In this case, based on the counter readings ie / 2 and / 2, the counters i and j are incremented in the direction of the right and lower picture edges and decremented in the direction of the left and upper picture edges.
  • the coordinates of the pixel can be taken over for the coordinates of the point of intersection, which component is a horizontal and a vertical line, that is to say a crossing center point. More precisely, the coordinate determination, if more pixels right and left, above and below are included in the coordinate determination in the form of a center of gravity calculation.
  • the coordinates of the intersection points are transformed back into the perspective of the camera and transferred to the geometric calculation.
  • the visual beams of the camera are assigned the intersection coordinates of the reflected beam with the screen plate via the 2D image processing. From this, no local altitude can yet be calculated for a single visual beam. As related to the Fig. 1 As already described, given a configuration, no local altitude can yet be calculated from a single visual beam of the camera to which the intersection point coordinates of the reflected beam and the screen plate are assigned via the 2D image processing.
  • an iterative method is used.
  • a whole bundle of visual rays is considered and provided that there are no cracks on the measurement object. If the resolution is sufficient, then the local gradients are coupled with the local heights at the location of the points of impingement of the visual rays on the measurement object.
  • the course of a model surface is preferably determined by the iterative method.
  • the model surface is described by a coefficient matrix. The coefficients of the model surface are calculated over the intersection coordinates of the reflected visual rays with the faceplate. In this case, a coefficient matrix for the model surface is given and from this the intersection points of the reflected rays with the screen plate are calculated.
  • the intersection coordinates of the reflected rays with the faceplate are calculated. Subsequently, the calculated coordinates are compared with the known grid coordinates of the screen. The coefficients of the model surface are now adjusted so that the difference between calculated and known coordinates is reduced as far as possible. The calculation and the comparison are repeated until a predetermined limit for the difference between measured and calculated is exceeded. As a solution method for this, also non-linear, Problem is the Levenberg-Marquardt method suitable. To calculate the intersection coordinates of the reflected visible rays with the screen plate, the simulation of the geometry of the measuring point on the computer is required. All calibration data are taken into account.
  • the Fig. 12 shows the sequence of the simulated measuring point. From the pixel coordinates of the detected intersection points of the grating and the parameters of the camera transformation, the visual beam vectors are calculated. This is followed by the calculation of the intersections of visual ray and model surface. At these points the normal vectors on the model surface are calculated. From the unit vectors of the visual rays and the flat normal, the reflection vector yields the reflection vector. Finally, the intersection of reflection vector and screen is calculated.
  • Fig. 13 shows the higher level signal flow plan.
  • the control loop structure can be clearly recognized.
  • the setpoint considered here is the constant object coordinates of the grid intersection points.
  • the measuring point represents the controlled system and is in accordance with Fig. 12 simulated.
  • the control deviation represents the difference between the object coordinates of the grid intersection points of the screen and the coordinates calculated in the model of the measuring point.
  • the nonlinear optimization acts as a controller and supplies the model parameters of the area as a manipulated variable.
  • the pixel coordinates of the grid intersection points of the camera image can be interpreted as a manipulated variable. If the control deviation is zero, the model surface and the real surface are the same.
  • Fig. 13 There are clearances for the arrangement in Fig. 13 ,
  • the structure chosen here results in the first line from the cross lattice.
  • the intersection points are also the interpolation points for the calculation of the model parameters.
  • the signals in Fig. 13 are vectors and matrices with significant dimensions.
  • parameter matrices of the dimension 12 x 12 to 20 x 20 are provided.
  • the vector equation (3) contains component equations, so that there is an indeterminate system of equations for solving for the unknowns p, ⁇ and the normal vector n (that is, a total of 4 unknowns).
  • the model surface is adapted and displaced until a model surface is formed and arranged such that the simulated observation beams reflected on the model surface strike the same LCD pixels as the actual surface to be measured were observed ( Fig. 15 ).
  • ⁇ n ⁇ a tensor product Bezier surface can be used.
  • B k n ⁇ n k ⁇ k ⁇ 1 - ⁇ n - k .
  • the b kl are the parameters of the model and the B k n the Berstein polynomials of degree n.
  • a parametric approach can be used for the bundle of visible beams, with which the visual direction vectors S uv can also be interpolated for non-integer indices u, v. This allows an analytical calculation of the normal vectors of the model surface: n ⁇ ij ⁇ ⁇ ⁇ uv ⁇ s uv ⁇ u ⁇ ⁇ ⁇ ⁇ uv ⁇ s uv ⁇ v ⁇

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Claims (9)

  1. Procédé d'inspection de surfaces, conçu pour détecter des défauts de surfaces et/ou pour mesurer la topographie de surfaces stables réfléchissantes, notamment de surfaces réfléchissantes de bandes métalliques, en particulier de bandes métalliques mises en mouvement, dans lequel
    - une caméra effectue un enregistrement d'un motif reproduit sur un écran et configuré de façon telle qu'il représente au moins des points d'intersection de lignes,
    - la direction d'observation de ladite caméra pointe vers une région de la surface réfléchissante,
    - la surface de l'écran sur laquelle le motif est reproduit est disposée, et tournée vers cette région, de telle sorte que la trajectoire des rayons d'observation de la caméra s'étende de ladite caméra jusqu'à ladite surface de l'écran, en transitant par la surface réfléchissante, et
    - ladite caméra est focalisée sur ladite surface de l'écran,
    - sachant que l'enregistrement est consigné en tant que matrice A dans laquelle la valeur respective aij correspond à la valeur mesurée que la caméra a enregistrée sur le site de pixellisation iij, la valeur maximale 1 de l'indice i correspondant au nombre des sites de pixellisation dans une première direction de propagation de la surface d'enregistrement de la caméra, et la valeur maximale J de l'indice j correspondant au nombre des sites de pixellisation dans une seconde direction de propagation,
    - ladite matrice A étant transformée, par binarisation, en une matrice B dans laquelle la valeur respective bij présente la valeur 1 ou 0,
    - l'image binaire, représentée par ladite matrice B, étant vouée à un procédé de squelettisation au cours duquel des tracés de lignes, le long desquels les valeurs bij sont identiques, sont déterminés dans un système de coordonnées dont les deux axes correspondent aux deux indices de ladite matrice, après quoi il est engendré un tableau de points d'intersection qui restitue la position spatiale occupée par des points d'intersection desdits tracés de lignes dans ledit système de coordonnées,
    - le profil d'une surface de modèle, se rapportant à la surface réfléchissante considérée, étant déterminé à l'aide d'un procédé itératif, sur la base dudit tableau de points d'intersection engendré à partir de l'enregistrement unique.
  2. Procédé d'inspection de surfaces, selon la revendication 1, caractérisé par le fait que la surface de modèle est représentée par un polynôme de Tchebychev bidimensionnel.
  3. Procédé d'inspection de surfaces, selon l'une des revendications 1 à 2, caractérisé par le fait que le point respectif d'intersection est consigné, dans le tableau de points d'intersection, avec une valeur d'indexage le définissant et avec ses coordonnées x et y dans un système de coordonnées.
  4. Procédé d'inspection de surfaces, selon l'une des revendications 1 à 3, caractérisé par le fait que le motif est porté de manière fixe sur l'écran.
  5. Procédé d'inspection de surfaces, selon l'une des revendications 1 à 3, caractérisé par le fait que le motif est projeté sur l'écran par l'intermédiaire d'un projecteur.
  6. Procédé d'inspection de surfaces, selon l'une des revendications 1 à 5, caractérisé par le fait que le motif comporte un réseau tramé homogène, et au moins un repère différant dudit réseau tramé homogène.
  7. Procédé d'inspection de surfaces, selon la revendication 6, caractérisé par le fait que le motif comporte un réseau tramé homogène, et un unique repère différant dudit réseau tramé homogène.
  8. Procédé d'inspection de surfaces, selon l'une des revendications 1 à 7, caractérisé par le fait que le motif présente un réseau entrecroisé dans lequel les intervalles d'entrecroisement sont de configuration non pas rectangulaire, mais circulaire.
  9. Procédé d'inspection de surfaces, selon l'une des revendications 1 à 8, caractérisé par le fait que la binarisation est exécutée en mode dynamique.
EP08012399.5A 2007-07-09 2008-07-09 Procédé d'inspection de surfaces destinée à détecter des défauts de surface et/ou mesurer la topographie de surface Not-in-force EP2031348B1 (fr)

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DE102007032113 2007-07-09

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EP2031348A1 EP2031348A1 (fr) 2009-03-04
EP2031348B1 true EP2031348B1 (fr) 2014-09-10

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ES (1) ES2526825T3 (fr)

Cited By (1)

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DE102020129040A1 (de) 2020-11-04 2022-05-05 Speira Gmbh Verfahren und Vorrichtung zur Erkennung von Oberflächenstrukturen

Families Citing this family (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
DE102010001715B4 (de) * 2010-02-09 2023-08-24 Robert Bosch Gmbh Verfahren und Vorrichtung zur Oberflächenprüfung
US20170178390A1 (en) * 2015-12-18 2017-06-22 Canon Kabushiki Kaisha Devices, systems, and methods for measuring and reconstructing the shapes of specular objects by multiview capture
DE102021108232A1 (de) 2021-03-31 2022-10-06 Carl Zeiss Industrielle Messtechnik Gmbh Messgerät zur 3D-Erfassung einer Oberfläche
CN113210461A (zh) * 2021-04-29 2021-08-06 中国重型机械研究院股份公司 一种带钢水平检查台及其使用方法

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